from sklearn_benchmarks.reporting.hp_match import HpMatchReporting
import pandas as pd
pd.set_option('display.max_colwidth', None)
pd.set_option('display.max_columns', None)
pd.set_option('display.max_rows', None)
reporting = HpMatchReporting(other_library="onnx", config="config.yml", log_scale=True)
reporting.make_report()
We assume here there is a perfect match between the hyperparameters of both librairies. For a given set of parameters and a given dataset, we compute the speedup
time scikit-learn / time onnx. For instance, a speedup of 2 means that onnx is twice as fast as scikit-learn for a given set of parameters and a given dataset.
KNeighborsClassifier_brute_force¶onnx (1.10.1) vs. scikit-learn (1.0.dev0)
All estimators share the following parameters: algorithm=brute.
predict
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | iteration_throughput | latency | n_jobs | n_neighbors | accuracy_score_sklearn | mean_duration_onnx | std_duration_onnx | accuracy_score_onnx | speedup | std_speedup | sklearn_profiling | onnx_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 100 | 2.017 | 0.041 | 0.000 | 0.002 | -1 | 1 | 0.676 | 20.326 | 0.126 | 0.676 | 0.099 | 0.099 | See | See |
| 1 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 100 | 0.023 | 0.003 | 0.000 | 0.023 | -1 | 1 | 0.000 | 0.354 | 0.010 | 0.000 | 0.066 | 0.066 | See | See |
| 2 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 100 | 3.106 | 0.046 | 0.000 | 0.003 | -1 | 5 | 0.743 | 20.393 | 0.027 | 0.743 | 0.152 | 0.152 | See | See |
| 3 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 100 | 0.025 | 0.002 | 0.000 | 0.025 | -1 | 5 | 1.000 | 0.354 | 0.011 | 1.000 | 0.070 | 0.070 | See | See |
| 4 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 100 | 2.384 | 0.005 | 0.000 | 0.002 | 1 | 100 | 0.846 | 20.109 | 0.020 | 0.846 | 0.119 | 0.119 | See | See |
| 5 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 100 | 0.021 | 0.000 | 0.000 | 0.021 | 1 | 100 | 1.000 | 0.367 | 0.008 | 1.000 | 0.056 | 0.056 | See | See |
| 6 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 100 | 3.119 | 0.050 | 0.000 | 0.003 | -1 | 100 | 0.846 | 20.266 | 0.195 | 0.846 | 0.154 | 0.154 | See | See |
| 7 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 100 | 0.026 | 0.004 | 0.000 | 0.026 | -1 | 100 | 1.000 | 0.363 | 0.007 | 1.000 | 0.071 | 0.071 | See | See |
| 8 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 100 | 2.375 | 0.005 | 0.000 | 0.002 | 1 | 5 | 0.743 | 20.052 | 0.041 | 0.743 | 0.118 | 0.118 | See | See |
| 9 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 100 | 0.020 | 0.000 | 0.000 | 0.020 | 1 | 5 | 1.000 | 0.365 | 0.010 | 1.000 | 0.055 | 0.055 | See | See |
| 10 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 100 | 1.252 | 0.016 | 0.001 | 0.001 | 1 | 1 | 0.676 | 20.651 | 0.200 | 0.676 | 0.061 | 0.061 | See | See |
| 11 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 100 | 0.019 | 0.000 | 0.000 | 0.019 | 1 | 1 | 0.000 | 0.351 | 0.010 | 0.000 | 0.055 | 0.055 | See | See |
| 12 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 2 | 1.744 | 0.032 | 0.000 | 0.002 | -1 | 1 | 0.845 | 4.357 | 0.011 | 0.845 | 0.400 | 0.400 | See | See |
| 13 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 2 | 0.008 | 0.002 | 0.000 | 0.008 | -1 | 1 | 1.000 | 0.286 | 0.005 | 1.000 | 0.028 | 0.028 | See | See |
| 14 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 2 | 2.964 | 0.022 | 0.000 | 0.003 | -1 | 5 | 0.883 | 4.287 | 0.022 | 0.883 | 0.691 | 0.691 | See | See |
| 15 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 2 | 0.011 | 0.005 | 0.000 | 0.011 | -1 | 5 | 1.000 | 0.289 | 0.005 | 1.000 | 0.037 | 0.037 | See | See |
| 16 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 2 | 2.311 | 0.002 | 0.000 | 0.002 | 1 | 100 | 0.887 | 4.328 | 0.009 | 0.887 | 0.534 | 0.534 | See | See |
| 17 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 2 | 0.004 | 0.000 | 0.000 | 0.004 | 1 | 100 | 1.000 | 0.286 | 0.004 | 1.000 | 0.012 | 0.012 | See | See |
| 18 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 2 | 2.991 | 0.038 | 0.000 | 0.003 | -1 | 100 | 0.887 | 4.341 | 0.026 | 0.887 | 0.689 | 0.689 | See | See |
| 19 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 2 | 0.010 | 0.003 | 0.000 | 0.010 | -1 | 100 | 1.000 | 0.287 | 0.005 | 1.000 | 0.036 | 0.036 | See | See |
| 20 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 2 | 2.337 | 0.027 | 0.000 | 0.002 | 1 | 5 | 0.883 | 4.281 | 0.024 | 0.883 | 0.546 | 0.546 | See | See |
| 21 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 2 | 0.004 | 0.000 | 0.000 | 0.004 | 1 | 5 | 1.000 | 0.287 | 0.006 | 1.000 | 0.012 | 0.012 | See | See |
| 22 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 2 | 1.113 | 0.007 | 0.000 | 0.001 | 1 | 1 | 0.845 | 4.347 | 0.012 | 0.845 | 0.256 | 0.256 | See | See |
| 23 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 2 | 0.002 | 0.000 | 0.000 | 0.002 | 1 | 1 | 1.000 | 0.287 | 0.004 | 1.000 | 0.008 | 0.008 | See | See |
KNeighborsClassifier_kd_tree¶onnx (1.10.1) vs. scikit-learn (1.0.dev0)
All estimators share the following parameters: algorithm=kd_tree.
predict
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | iteration_throughput | latency | n_jobs | n_neighbors | accuracy_score_sklearn | mean_duration_onnx | std_duration_onnx | accuracy_score_onnx | speedup | std_speedup | sklearn_profiling | onnx_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | 1.699 | 0.009 | 0.000 | 0.002 | 1 | 5 | 0.975 | 122.443 | 0.000 | 0.975 | 0.014 | 0.014 | See | See |
| 1 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 10 | 0.002 | 0.000 | 0.000 | 0.002 | 1 | 5 | 1.000 | 3.060 | 0.028 | 1.000 | 0.001 | 0.001 | See | See |
| 2 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | 0.967 | 0.011 | 0.000 | 0.001 | -1 | 5 | 0.975 | 121.677 | 0.000 | 0.975 | 0.008 | 0.008 | See | See |
| 3 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 10 | 0.003 | 0.001 | 0.000 | 0.003 | -1 | 5 | 1.000 | 3.067 | 0.049 | 1.000 | 0.001 | 0.001 | See | See |
| 4 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | 0.512 | 0.007 | 0.000 | 0.001 | -1 | 1 | 0.964 | 122.636 | 0.000 | 0.964 | 0.004 | 0.004 | See | See |
| 5 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 10 | 0.003 | 0.000 | 0.000 | 0.003 | -1 | 1 | 1.000 | 3.075 | 0.042 | 1.000 | 0.001 | 0.001 | See | See |
| 6 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | 0.892 | 0.015 | 0.000 | 0.001 | 1 | 1 | 0.964 | 127.365 | 0.000 | 0.964 | 0.007 | 0.007 | See | See |
| 7 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 10 | 0.001 | 0.000 | 0.000 | 0.001 | 1 | 1 | 1.000 | 3.071 | 0.069 | 1.000 | 0.000 | 0.000 | See | See |
| 8 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | 5.390 | 0.058 | 0.000 | 0.005 | 1 | 100 | 0.973 | 126.638 | 0.000 | 0.973 | 0.043 | 0.043 | See | See |
| 9 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 10 | 0.004 | 0.001 | 0.000 | 0.004 | 1 | 100 | 1.000 | 3.103 | 0.082 | 1.000 | 0.001 | 0.001 | See | See |
| 10 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | 2.928 | 0.024 | 0.000 | 0.003 | -1 | 100 | 0.973 | 127.925 | 0.000 | 0.973 | 0.023 | 0.023 | See | See |
| 11 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 10 | 0.005 | 0.001 | 0.000 | 0.005 | -1 | 100 | 1.000 | 3.073 | 0.071 | 1.000 | 0.002 | 0.002 | See | See |
| 12 | KNeighborsClassifier_kd_tree | predict | 1000 | 1000 | 2 | 0.023 | 0.000 | 0.001 | 0.000 | 1 | 5 | 0.923 | 0.047 | 0.001 | 0.923 | 0.493 | 0.493 | See | See |
| 13 | KNeighborsClassifier_kd_tree | predict | 1000 | 1 | 2 | 0.001 | 0.000 | 0.000 | 0.001 | 1 | 5 | 1.000 | 0.006 | 0.000 | 1.000 | 0.110 | 0.110 | See | See |
| 14 | KNeighborsClassifier_kd_tree | predict | 1000 | 1000 | 2 | 0.026 | 0.000 | 0.001 | 0.000 | -1 | 5 | 0.923 | 0.046 | 0.000 | 0.923 | 0.564 | 0.564 | See | See |
| 15 | KNeighborsClassifier_kd_tree | predict | 1000 | 1 | 2 | 0.002 | 0.000 | 0.000 | 0.002 | -1 | 5 | 1.000 | 0.006 | 0.000 | 1.000 | 0.386 | 0.386 | See | See |
| 16 | KNeighborsClassifier_kd_tree | predict | 1000 | 1000 | 2 | 0.024 | 0.000 | 0.001 | 0.000 | -1 | 1 | 0.895 | 0.045 | 0.000 | 0.895 | 0.535 | 0.535 | See | See |
| 17 | KNeighborsClassifier_kd_tree | predict | 1000 | 1 | 2 | 0.003 | 0.001 | 0.000 | 0.003 | -1 | 1 | 1.000 | 0.006 | 0.000 | 1.000 | 0.421 | 0.421 | See | See |
| 18 | KNeighborsClassifier_kd_tree | predict | 1000 | 1000 | 2 | 0.021 | 0.000 | 0.001 | 0.000 | 1 | 1 | 0.895 | 0.045 | 0.000 | 0.895 | 0.473 | 0.473 | See | See |
| 19 | KNeighborsClassifier_kd_tree | predict | 1000 | 1 | 2 | 0.001 | 0.000 | 0.000 | 0.001 | 1 | 1 | 1.000 | 0.006 | 0.000 | 1.000 | 0.112 | 0.112 | See | See |
| 20 | KNeighborsClassifier_kd_tree | predict | 1000 | 1000 | 2 | 0.039 | 0.000 | 0.000 | 0.000 | 1 | 100 | 0.919 | 0.073 | 0.003 | 0.919 | 0.536 | 0.536 | See | See |
| 21 | KNeighborsClassifier_kd_tree | predict | 1000 | 1 | 2 | 0.001 | 0.000 | 0.000 | 0.001 | 1 | 100 | 1.000 | 0.006 | 0.000 | 1.000 | 0.113 | 0.113 | See | See |
| 22 | KNeighborsClassifier_kd_tree | predict | 1000 | 1000 | 2 | 0.040 | 0.000 | 0.000 | 0.000 | -1 | 100 | 0.919 | 0.071 | 0.000 | 0.919 | 0.563 | 0.563 | See | See |
| 23 | KNeighborsClassifier_kd_tree | predict | 1000 | 1 | 2 | 0.002 | 0.000 | 0.000 | 0.002 | -1 | 100 | 1.000 | 0.006 | 0.000 | 1.000 | 0.394 | 0.394 | See | See |
HistGradientBoostingClassifier_best¶onnx (1.10.1) vs. scikit-learn (1.0.dev0)
All estimators share the following parameters: learning_rate=0.01, n_iter_no_change=10.0, max_leaf_nodes=100.0, max_bins=255.0, min_samples_leaf=100.0, max_iter=300.0.
predict
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | n_iter | iteration_throughput | latency | accuracy_score_sklearn | mean_duration_onnx | std_duration_onnx | accuracy_score_onnx | speedup | std_speedup | sklearn_profiling | onnx_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | HistGradientBoostingClassifier_best | predict | 100000 | 1000 | 100 | 0.144 | 0.002 | 300 | 0.006 | 0.000 | 0.798 | 0.520 | 0.020 | 0.798 | 0.277 | 0.277 | See | See |
| 1 | HistGradientBoostingClassifier_best | predict | 100000 | 1 | 100 | 0.019 | 0.001 | 300 | 0.000 | 0.019 | 1.000 | 0.432 | 0.013 | 1.000 | 0.043 | 0.043 | See | See |